SU‐FF‐T‐03: 3D Characterization of Small Megavoltage Radiation Fields Using An Optical CT Scanner with Ferrous Xylenol Orange Gels
Bibliographic record
Abstract
Purpose: To investigate the feasibility of using a 3D dosimetry system consisting of a radiochromic ferrous xylenol orange (FX) gel and a prototype commercial cone beam optical‐CT scanning system (Vista™, Modus Medical Devices, Inc., London, ON) to dosimetrially characterize small megavoltage photon fields. Method and Materials: An FXG gel was irradiated using 6MV x‐ray fields (30, 10 and 5mm diameter) produced via custom stereotactic collimators mounted on a Varian Clinac 2100EX accelerator. Measurements were also completed using radiochromic (Gafchromic EBT) and radiographic (Kodak EDR2) film, and a Exradin #a1SL ion chamber for comparison purposes. The gel was optically CT scanned 10, 20, 30 and 40 minutes post‐irradiation to assess the effects of xylenol orange/ferric ion complex diffusion in gel. Lateral dose profiles and percentage depth dose (PDD) curves were extracted from the 3D image data sets for analysis. Results: FX gels together with fast optical CT scanning allows for the measurement of all dosimetric parameters required as pencil beam input for treatment planning systems in a single irradiation. The experimental set‐up is simple, and the gel allows for dose measurements in a tissue‐equivalent and energy‐independent medium. Lateral beam profiles as measured in the FXG gel matched those measured using both types of film within 2 mm. PDD curves measured with gel and ion chamber were also in good agreement (within 3 mm) up to 65mm depth. Conclusion: The radiochromic FX gel and fast optical CT scanner is a promising dosimetry system for the characterization of small x‐ray fields for the purposes of commissioning treatment planning systems. The advantage is that a full 3D data set can be acquired quickly and efficiently. Conflict of Interest: Two of the authors (KJ and JB) have a licensing agreement with Modus Medical Devices, Inc. for the commercialization of the Vista™ scanner.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".